The AIMOps project will advance artificial intelligence for manufacturing by developing integrated AI architectures that improve predictive and prescriptive decision-making at system level. The project is designed to harness multimodal data—spanning production, maintenance, and quality domains—to create scalable AI models that address the complexity of real shop-floor environments. Key outcomes include the architectural design of robust AI models, prototype development, and the deployment of these solutions through mature MLOps practices with a focus on long-term lifecycle management. By facilitating proactive, data-driven decisions, AIMOps aims to increase productivity, reduce downtime, enhance product quality, and decrease operational costs. These innovations will reinforce Sweden’s leadership in industrial AI, providing tools and frameworks that foster ongoing industrial innovation and competitiveness. The project brings together academic and industrial partners to validate its outcomes in real-world manufacturing scenarios, with broad knowledge dissemination to foster adoption and impact.